Staff Data Scientist Solutions Design Team!

Key Skills

Big Data Technology, Cloud computing, Data Analytics, Data Modeling, Data science techniques, Deep Learning, Design, Leadership Skill, Machine learning techniques, Mentoring, Natural Language Processing (NLP), Predictive Modeling, Project management, Python Programming, R Programming, Scala Programming, Teamwork

Job Description

Staff Data Scientist

Identifying, tracking and solving defects is critical for any organization’s sustainable success. Unresolved defects impact customer loyalty and create friction for its employees.

In this role you will:

• Utilize big data within a variety of sources to solve customer and associates’ highest impact defects. Train algorithms so they can be applied to future data sets and provide the appropriate search results.

• Leverage machine learning and artificial intelligence to increase insight and trend analysis.

• Partner with our data analytics teams to develop best-in-class capabilities to identify defects programmatically, proactively and intelligently.

• Conduct advanced statistical analysis to determine trends and significant data relationships. Enable root cause analysis and case management to eliminate defects.

• Ensure final deliverables of our capability is actionable and communicated in a way that drives quantifiable business benefit in terms of improved decision making and solution prioritization.

• Depending on the problem, build time Series, computer vision, NLP or basic predictive models.

• Research new trends in the industry and utilizing up-to-date technology.

• Examples of deliverables could range from data modeling, decision making engines, anomaly detection throughout the enterprise, and predictive /prescriptive capabilities.

Desired Skills and Experience:

• 5+ years of relevant Data Science experience

• Bachelor of Science and 5 years' data science experience OR Master of Science and 3 years' data science experience.

• Supervised and unsupervised machine learning.

• Model governance.

• Model monitoring.

• Strong production deployment background.

• Strong in Python coding.

• NLP and or Deep Learning skills.

• Cloud Experience.

• Mentoring and leading junior data scientists

• Strong communicator

• Cross functional leadership

Minimum Qualifications...

Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics related field. Option 3: 6 years' experience in an analytics or related field

Preferred Qualifications...

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.

Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch)

Primary Location...

702 SW 8TH ST, BENTONVILLE, AR 72716, United States of America

About Walmart

At Walmart, we help people save money so they can live better. This mission serves as the foundation for every decision we make, from responsible sourcing to sustainability—and everything in between. As a Walmart associate, you will play an integral role in shaping the future of retail, tech, merchandising, finance and hundreds of other industries—all while affecting the lives of millions of customers all over the world. Here, your work makes an impact every day. What are you waiting for?

Walmart, Inc. is an Equal Opportunity Employer- By Choice. We believe we are best equipped to help our associates, customers, and the communities we serve live better when we really know them. That means understanding, respecting, and valuing diversity- unique styles, experiences, identities, abilities, ideas and opinions- while being inclusive of all people.